This package contains the files required to reproduce the results of Jaakkola & Millner (2020): Non-dogmatic climate policy (in Journal of the Association of Environmental and Resource Economists).

Code copyright (C) 2022 Niko Jaakkola, Antony Millner.

Contents
--------

Nondogmatic_climate.ipynb
  Julia 1.0.5 source code required to reproduce the results in the paper, conduct
  diagnostics, and more.

Y500T10N10 [Folder]
  This folder contains the files used to compute the benchmark run. The folder also contains
  associated files which can be used to reproduce the graphs or verify results without
  having to solve the model again.

Y500T10N10robust [Folder]
  As above, but used to solve the model in the case in which switching probabilities
  depend on the Mahalanobis distance between different types.

clusters.m
  A Matlab script to reduce the preference data of Drupp et al. (2018) into a given
  number of clusters.

transitions.m
  A Matlab script to compute the transition probabilities, given a set of clusters.
  Note that the clusters and transition probabilities used in for the published version
  of the paper have already been computed and included in the data folders above, as
  'preferences.csv'.  To recompute the clusters and transitions (for example if using
  updated data), the output of transitions.m should be renamed 'preferences.csv' and
  saved in the appropriately named data folder.

deltaeta_data.mat
  Contains the preference data from the survey by Drupp et al. (2018).


Notes
-----

The Julia notebook has not been fully automated.  Rather, the code is divided into
separate blocks of code which need to be manually run to produce output.  These blocks
are further grouped into 'tasks' (e.g. Model initialisation, Solving the model, Computing
trajectories, Plotting, etc.).  Using the model requires some familiarisation with the
structure of the code, but mostly a task is executed by running the code blocks within
any given task from beginning to end, with the exception of code blocks used to save/load
data which are skipped or executed as required.

The code blocks are documented.  Running the model should be relatively straightforward
following the instructions.  Note that various files used to save model results
(e.g. the model solution, and the computed Monte Carlo run) are provided to verify the
results in the paper.  However, these can also be computed from scratch using the code.
Of course reproducing the exact results for the Monte Carlo run requires the (random)
type trajectories to be exactly the same (i.e. the ones we provide).

For assistance, please contact Niko Jaakkola:
niko.jaakkola@unibo.it
https://sites.google.com/view/jaakkola
